{"id":"W1481493156","doi":"","title":"Optimization in 2 m 3 n Factorial Experiments","year":2012,"lang":"en","type":"article","venue":"Algorithmic operations research","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Integer programming; Factorial experiment; Post hoc; Factorial; Design of experiments; Mathematical optimization; Orthogonal array; Theoretical computer science; Industrial engineering; Algorithm; Mathematics; Machine learning; Taguchi methods; Engineering; Statistics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02707644,0.001860965,0.003025192,0.001206196,0.0008054647,0.001865392,0.001826952,0.00153888,0.003038281],"category_scores_gemma":[0.04036488,0.001479337,0.002226301,0.001866889,0.00309465,0.00188651,0.001961894,0.001696116,0.0004400799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002804493,"about_ca_system_score_gemma":0.003645218,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001850069,"about_ca_topic_score_gemma":0.00248416,"domain_scores_codex":[0.9595641,0.03424145,0.001095359,0.002756364,0.001735892,0.000606903],"domain_scores_gemma":[0.9535488,0.04115858,0.002463419,0.001710244,0.0008254633,0.000293573],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001210488,0.0003713207,0.001579842,0.001616716,0.0004196404,0.0002024697,0.0002999397,0.6506925,0.004571182,0.2158107,0.001611354,0.121614],"study_design_scores_gemma":[0.0004475489,0.001559807,0.001245356,0.0001077085,0.0001079865,0.00006571824,0.00007946775,0.7689641,0.002990894,0.2193359,0.005022605,0.00007289151],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0092253,0.0004112303,0.9877751,0.0001916202,0.00003198104,0.0003150551,0.00006624944,0.0001129056,0.001870542],"genre_scores_gemma":[0.1470989,0.0004835716,0.8477787,0.0002223629,0.00006403502,0.00255719,0.0001162196,0.00006402567,0.001614906],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02707644,"threshold_uncertainty_score":0.1431956,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5038899504498755,"score_gpt":0.6029256541613165,"score_spread":0.09903570371144099,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}